System and method to optimize workflow

ABSTRACT

The present disclosure describes a system and method to reduce the overall time taken to complete distributed process workflows. Each workflow can include multiple actions that are completed by or at different client devices. The actions of a workflow can be dependent on prior actions in the workflow. For example, a second client device may not be able to complete a second action until a first client device completes a first action in the workflow. The system can predict time periods and the geolocations where client devices are most likely to complete an assigned action. Using the selected time periods and geolocations, the system can transmit notifications to the client devices when the action is most likely to be completed.

BACKGROUND

Workflows can include a plurality of computational actions. Thecomputational actions can be performed by one or more devices within anetworked environment. In some implementations, the computationalactions need to be completed in an ordered sequence. For example, afirst action may need to be completed before a second action can bestarted. The sequential nature of the computational actions within theworkflow can cause backlogs of actions to be completed at clientdevices. The growing backlog of actions can cause an increase in thetime required to complete a workflow.

BRIEF SUMMARY OF THE DISCLOSURE

The present disclosure describes a system and method to reduce theoverall time taken to complete distributed process workflows. Eachworkflow can include multiple actions that are completed by or atdifferent client devices. The actions of a workflow can be dependent onprior actions in the workflow. For example, a second client device maynot be able to complete a second action until a first client devicecompletes a first action in the workflow. The system can predict timeperiods and the geolocations where client devices are most likely tocomplete an assigned action. Using the selected time periods andgeolocations, the system can transmit notifications to the clientdevices when the action is most likely to be completed.

According to at least one aspect of the disclosure, a system to reducetransmission times in a networked system can include a memory storingprocessor executable instructions and one or more processors. The systemcan generate a notification message indicating a first action to beperformed in a distributed process. The system can identify a pluralityof features associated with the first action to be performed in thedistributed process. The system can select a plurality of time windowsfor each of a plurality of device locations based at least on theplurality of features. The system can determine a confidence value foreach of the plurality of time windows. The confidence value indicating alikelihood of the first action being completed during each of therespective plurality of time windows. The system can select a timewindow from the plurality of time windows for one of the plurality ofdevice locations based at least on the confidence value of the timewindow. The system can transmit the notification message to a devicelocated at the one of the plurality of device locations after a starttime of the time window.

The system can determine a time duration of the time window. The systemcan hold the notification message until a predetermined device entersthe one of the plurality of device locations based on the time durationbeing below a predetermined threshold. The system can determine apredetermined device is not within the one of the plurality of devicelocations at the end of the time window, and can transmit thenotification message to the device at the end of the time window.

The system can prefetch content associated with the first action to thedevice before the start time of the time window. The system can receivelocation information of the device and select the time window from theplurality of time windows based on the location information of thedevice.

The system can generate a second notification message indicating asecond action to be performed in the distributed process. The system cantransmit the second notification message to a second device. The systemcan transmit a third notification message indicating a third action tobe performed in the distributed process to a third device beforereceiving an indication that the second device completed the secondaction.

The system can select a second time window from the plurality of timewindows. The second time window can have a time duration shorter thanthe time window and can be associated with a second device location. Thesystem can transmit the notification message to a second device at thesecond device location. The system can transmit the notification messageto the device located at the one of the plurality of device locationsbased on not receiving an indication that the device at the seconddevice location completed the second action.

The plurality of features can include at least one of locationinformation, an action duration, a historical usage, a time zone, or auser designation. The confidence value for each of the plurality of timewindows at each of the plurality of device locations can be generatedusing a machine learning based regression algorithm.

According to at least one aspect of the disclosure, a method to reducetransmission times in a networked system can include generating anotification message indicating a first action to be performed in adistributed process. The method can include determining a plurality offeatures associated with the first action to be performed in thedistributed process. The method can include select a plurality of timewindows for each of a plurality of device locations based at least onthe plurality of features. The method can include determining aconfidence value for each of the plurality of time windows. Theconfidence value can indicate a likelihood of the first action beingcompleted during each of the respective plurality of time windows. Themethod can include selecting a time window from the plurality of timewindows for one of the plurality of device locations based at least onthe confidence value of the time window. The method can includetransmitting the notification message to a device located at the one ofthe plurality of device locations after a start time of the time window.

The method can include determining a time duration of the time window.The method can include holding the notification message until apredetermined device enters the one of the plurality of device locationsbased on the time duration being below a predetermined threshold. Themethod can include determining that a predetermined device is not withinthe one of the plurality of device locations at the end of the timewindow. The method can include transmitting the notification message tothe device at the end of the time window. The method can includeprefetching content associated with the first action to the devicebefore the start time of the time window.

The method can include receiving location information of the device. Themethod can include selecting the time window from the plurality of timewindows based on the location information of the device. The method caninclude generating a second notification message indicating a secondaction to be performed in the distributed process. The method caninclude transmitting the second notification message to a second device.The method can include transmitting a third notification messageindicating a third action to be performed in the distributed process toa third device before receiving an indication that the second devicecompleted the second action.

The method can include selecting a second time window from the pluralityof time windows. The second time window can have a time duration shorterthan the time window and can be associated with a second devicelocation. The method can include transmitting the notification messageto a second device at the second device location.

The method can include transmitting the notification message to thedevice located at the one of the plurality of device locations based onnot receiving an indication that the device at the second devicelocation completed the second action. The plurality of features caninclude at least one of location information, an action duration, ahistorical usage, a time zone, or a user designation. The confidencevalue for each of the plurality of time windows at each of the pluralityof device locations can be generated using a machine learning basedregression algorithm.

BRIEF DESCRIPTION OF THE FIGURES

The foregoing and other objects, aspects, features, and advantages ofthe present solution will become more apparent and better understood byreferring to the following description taken in conjunction with theaccompanying drawings, in which:

FIG. 1 illustrates a block diagram of an embodiment of a computingdevice;

FIG. 2 illustrates a system to reduce transmission times in a networkedsystem; and

FIG. 3 illustrates a block diagram of an example method to reduce thetime to complete distributed processes.

The features and advantages of the present solution will become moreapparent from the detailed description set forth below when taken inconjunction with the drawings, in which like reference charactersidentify corresponding elements throughout. In the drawings, likereference numbers generally indicate identical, functionally similar,and/or structurally similar elements.

DETAILED DESCRIPTION

For purposes of reading the description of the various embodimentsbelow, the following descriptions of the sections of the specificationand their respective contents may be helpful:

Section A describes a computing environment which may be useful forpracticing embodiments described herein; and

Section B describes systems and methods reducing completion times ofdistributed processes.

A. Computing Environment

Prior to discussing the specifics of embodiments of the systems andmethods to reduce transmission times in a networked system, it may behelpful to discuss the computing environments in which such embodimentsmay be deployed.

As shown in FIG. 1, computer 101 may include one or more processors 103,volatile memory 122 (e.g., random access memory (RAM)), non-volatilememory 128 (e.g., one or more hard disk drives (HDDs) or other magneticor optical storage media, one or more solid state drives (SSDs) such asa flash drive or other solid state storage media, one or more hybridmagnetic and solid state drives, and/or one or more virtual storagevolumes, such as a cloud storage, or a combination of such physicalstorage volumes and virtual storage volumes or arrays thereof), userinterface (UI) 123, one or more communications interfaces 118, andcommunication bus 150. User interface 123 may include graphical userinterface (GUI) 124 (e.g., a touchscreen, a display, etc.) and one ormore input/output (I/O) devices 126 (e.g., a mouse, a keyboard, amicrophone, one or more speakers, one or more cameras, one or morebiometric scanners, one or more environmental sensors, one or moreaccelerometers, etc.). Non-volatile memory 128 stores operating system115, one or more applications 116, and data 117 such that, for example,computer instructions of operating system 115 and/or applications 116are executed by processor(s) 103 out of volatile memory 122. In someembodiments, volatile memory 122 may include one or more types of RAMand/or a cache memory that may offer a faster response time than a mainmemory. Data may be entered using an input device of GUI 124 or receivedfrom I/O device(s) 126. Various elements of computer 101 may communicatevia one or more communication buses, shown as communication bus 150.

Computer 101 as shown in FIG. 1 is shown merely as an example, asclients, servers, intermediary and other networking devices and may beimplemented by any computing or processing environment and with any typeof machine or set of machines that may have suitable hardware and/orsoftware capable of operating as described herein. Processor(s) 103 maybe implemented by one or more programmable processors to execute one ormore executable instructions, such as a computer program, to perform thefunctions of the system. As used herein, the term “processor” describescircuitry that performs a function, an operation, or a sequence ofoperations. The function, operation, or sequence of operations may behard coded into the circuitry or soft coded by way of instructions heldin a memory device and executed by the circuitry. A “processor” mayperform the function, operation, or sequence of operations using digitalvalues and/or using analog signals. In some embodiments, the “processor”can be embodied in one or more application specific integrated circuits(ASICs), microprocessors, digital signal processors (DSPs), graphicsprocessing units (GPUs), microcontrollers, field programmable gatearrays (FPGAs), programmable logic arrays (PLAs), multi-core processors,or general-purpose computers with associated memory. The “processor” maybe analog, digital or mixed-signal. In some embodiments, the “processor”may be one or more physical processors or one or more “virtual” (e.g.,remotely located or “cloud”) processors. A processor including multipleprocessor cores and/or multiple processors multiple processors mayprovide functionality for parallel, simultaneous execution ofinstructions or for parallel, simultaneous execution of one instructionon more than one piece of data.

Communications interfaces 118 may include one or more interfaces toenable computer 101 to access a computer network such as a Local AreaNetwork (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN),or the Internet through a variety of wired and/or wireless or cellularconnections.

In described embodiments, the computing device 101 may execute anapplication on behalf of a user of a client computing device. Forexample, the computing device 101 may execute a virtual machine, whichprovides an execution session within which applications execute onbehalf of a user or a client computing device, such as a hosted desktopsession. The computing device 101 may also execute a terminal servicessession to provide a hosted desktop environment. The computing device101 may provide access to a computing environment including one or moreof: one or more applications, one or more desktop applications, and oneor more desktop sessions in which one or more applications may execute.

Additional details of the implementation and operation of networkenvironment, computer 101 and client and server computers may be asdescribed in U.S. Pat. No. 9,538,345, issued Jan. 3, 2017 to CitrixSystems, Inc. of Fort Lauderdale, Fla., the teachings of which arehereby incorporated herein by reference.

B. Systems and Methods Reducing Completion Times of DistributedProcesses

The present disclosure describes a system and method to reduce theoverall time taken to complete distributed process workflows. A workflowcan include multiple actions that, in some examples, must be completedin a predetermined order. Based on a first action being completed, thesystem can transmit a notification message (which can also be referredto as a notification or a message) to a second client device indicatingthat work can begin on a second action in the workflow. For example, thedistributed process can be a document review process that can includethe generation of a document by a first user at a first client device,review of the document by a second user a second client device, andapproval by a third user at a third client device. Each of the clientdevices can be located at different locations and in different timezones. Completion of the document generation by the first user can causethe system to transmit a notification to the second user's client deviceindicating that the second user can begin the second action of reviewingthe document generated during the first action.

Because the first user may complete the first action (causing anotification about the second action to be transmitted to the secondclient device) at a time when the second user cannot work on the secondaction the notification may be ignored by the second user. For example,notification may be missed because the user is not at the client deviceor because the notification can be deprioritized by later arrivingnotifications. In another example, the second user may be in a differenttime zone than the first user, which can cause the notification of thesecond action to reach the second user's client device when the seconduser is not at work. In some implementations, users may be associatedwith multiple locations and/or client devices. In these cases, thesystem may to select to which of the locations or client devices thenotification should be transmitted. Because the notifications forsubsequent actions can reach client devices and users when the actionsassociated with the notifications cannot be acted upon, the total timeto complete a workflow can be reduced by holding and transmittingnotifications to client devices and user when the user can act on theactions associated with the notification. Predicting when and at whichclient device a user will complete an action can also enable the systemto prefetch data or content associated with the action to the respectiveclient device. This can save bandwidth compared to prefetching the datato each of the client devices associated with the user.

FIG. 2 illustrates a system 200 to reduce transmission times in anetworked system. The system 200 can include one or more servers 202,which can be data processing systems. The server 202 can communicatewith a plurality of client devices 212(1)-212(N) (which can collectivelybe referred to as client devices 212) via a network 214. The server 202can include a notification generator 204, a scoring engine 206, afeature identifier 208, scheduling engine 210, an action generator 216,and a database 218.

The server 202 can be one or more of the computers 101 or other dataprocessing systems. The server 202 can include memory 128 that storesone or more applications 116. The applications 116 can includemachine-readable instructions to perform the functions performed by theserver 202. The server 202 can execute applications 116, scripts, orother machine-readable instructions such as the notification generator204, scoring engine 206, feature identifier 208, scheduling engine 210,and an action generator 216. The server 202 can communicate with aplurality of client devices 212 via the network 214.

The server 202 and client devices 212 can communicate via one or moreelectronic communication links that can form the network 214. Thenetwork 214 can be a local-area network (LAN) (e.g., a companyIntranet), a metropolitan area network (MAN), a wide area network (WAN)(e.g., the Internet), or any combination thereof.

The system 200 can include a plurality of client devices 212 thatcommunicate with the server 202 via the network 214. Each of the clientdevices 212 can be an instance of the computer 101 described in relationto FIG. 1. The client devices 212 can include one or more processorsconfigured to execute machine-readable instructions. The client devices212 can include one or more of a desktop computer, a laptop computer, ahandheld computer, a tablet computing platform, a NetBook, a mobiledevice, a gaming console, and/or other computing platforms.

The server 202 can include an action generator 216. The action generator216 can be any script, file, program, application, set of instructions,or computer-executable code, that is configured to enable a computingdevice on which the action generator 216 is executed to generate theactions of a distributed process. The action generator 216 can generatedistributed processes to complete computational processes. The actiongenerator 216 can divide a distributed process in to a plurality ofactions. The server 202 can assign each of the actions to a differentone of the client devices 212 for execution or completion. A distributedprocess can be any computational processes that can be divided into aplurality of sub-tasks. The distributed process can be a computationalcalculation that is divided into sub-tasks and each of the sub-tasks areexecuted by a client device 212. The distributed process can be aworkflow. The workflow can include a plurality of sub-tasks that arecompleted by a client device 212 or a user using the client device 212.A workflow can include document generation, which can include sub-tasksor actions that can include initial generation, review, editing,approval, and authorization. The workflow for the generation of aweb-based document can be managed by the server 202. The actiongenerator 216 can divide the workflow into the actions (e.g., review,editing, approval, etc.). Each action can be assigned to a user orclient device 212.

In some implementations, the actions can have a serial order such that afirst action must be completed before a subsequent action can bestarted. For example, a review and edit action may need to be completedbefore the final web-based document can be approved by via a secondclient device 212. In some implementations, actions can be executed inparallel such that different client devices 212 can execute differentactions at substantially the same time. For example, the actiongenerator 216 can generate a distributed process to generate electronicdocuments. In some implementations, actions can be optional. Forexample, reviewing a document by a user may be optional and the server202 can transmit a notification of a subsequent action to another clientdevice 212 prior to receiving an indication that the review action wascompleted. The action generator 216 can divide the document generationdistributed process into separate actions, such as creating a document;reviewing the document; and approving the document. The actions ofreviewing the document can be sent to multiple users at multiple clientdevices 212 that can review the document in parallel.

Once the action generator 216 generates the actions of a workflow, theaction generator 216 can store each of the actions in the actiondatabase 218. The actions can be stored in the action database 218 as adata structure that includes the workflow to which the action belongs, auser or client device 212 assigned to the action, the action type, atrigger for starting the action, a requirement flag, a notification timeand location, and a completion status. The notification time andlocation can be determined and provided by the scheduling engine 210, asdescribed below. The trigger for starting the action can be anindication of actions or conditions that must be met before the givenaction can begin. For example, the trigger for an approval action can bethat all required, previous actions in the workflow are completed (e.g.,their completion status is flagged as done). The requirement flag in thedata structure can indicate whether the action is a required action. Forexample, the review action may not need to be completed by each user.The notification location data in the data structure can indicate aphysical location where a notification associated with the action shouldbe transmitted to the assigned client device 212. The notification timedata can indicate when (either a specific time or a range of times) ofwhen the notification relating to an action should be transmitted to aclient device 212.

The server 202 can include a notification generator 204. Thenotification generator 204 can be any script, file, program,application, set of instructions, or computer-executable code, that isconfigured to enable a computing device on which the notificationgenerator 204 is executed to generate notification messages related toone or more actions of a workflow. The notification generator 204 can beconfigured to generate a notification message for each of the actions ina workflow generated by the action generator 216. For example, thenotification generator 204 can generate a first notification for a firstaction to be performed in a distributed process, a second notificationfor a second action in the distributed process, etc. The notificationgenerator 204 can process the workflow data structure generated by theaction generator 216 and stored in the action database 218 to determinethe content of the notification, the recipient client device 212 of thenotification, and the transmission parameters of the notification. Thetransmission parameters can indicate a time (or time window) when thenotification generator 204 should transmit the notification to theclient device 212. The notification parameters can indicate a locationparameter. The location parameter can be a geo-fence within which theclient device 212 needs to be for the notification generator 204 totransmit the notification to the client device 212.

For example, the notification generator 204 can include a transmissionmodule and can transmit the notification to a client device 212 when theclient device 212 at the start of the time window associated with theaction, at the end of the time window associated with the action, or ata time within the time window associated with the action. Thenotification generator 204 can be configured to transmit thenotification to the client device 212 when the client device 212 entersor exits the geo-fence associated with the location parameter of thetransmission parameters.

The notification generator 204 can generate the notification as an emailmessage, text message, push notification, chat message, or other form ofdigital message. The notification can be transmitted to the clientdevice 212 via a specific application executing on the client device212. For example, the notification can be transmitted within the chat ormessaging functionality of a program associated with the action. In thisexample, if the workflow is for the generation of a web-based document,the notification generator 204 can transmit the notification to theclient device 212 within the chat functionality of the application forediting the web-based document.

The notification generator 204 can hold, pause, or delay thetransmission of a notification until the transmission parameters havebeen achieved. For example, when the transmission parameters require theclient device 212 to be within a specific geolocation, the notificationgenerator 204 can hold the notification until the client device 212enters the geolocation.

The server 202 can include a feature identifier 208. The featureidentifier 208 can be any script, file, program, application, set ofinstructions, or computer-executable code, that is configured to enablea computing device on which the feature identifier 208 is executed todetermine a plurality of features associated with the actions of theworkflow. The features for an action can indicate parameters of theaction, parameters for completing the action, parameters of the clientdevice 212 assigned to complete the action, parameters of a clientdevice 212 or user to which the action should be assigned, or anycombination thereof. For example, the features can include a geolocationin which the action can be complete, a geolocation of the client device212 to which the feature is assigned, a type of the action, a durationof the action (e.g., an estimate of the time it should take to completethe action), a due date of the action, a designation or role of theclient device 212 or user assigned to the action, historical usageassociated with the client device 212 or user assigned to the action,historical usage associated with the type of action (e.g., is the actiontype generally completed on time or within a specific geo-fence), ortime zones associated with the client device 212 or user assigned theaction. The feature identifier 208 can determine the features for anaction based on historical data associated with actions of the same typeor actions assigned to the same user or client device 212.

The server 202 can include a scoring engine 206. The scoring engine 206can be any script, file, program, application, set of instructions, orcomputer-executable code, that is configured to enable a computingdevice on which the scoring engine 206 is executed to calculateconfidence levels for the action time windows and geolocations. Theconfidence level can indicate a likelihood that a client device 212 oruser will complete the action at a given location or within a given timewindow. The scoring engine 206 can use a machine learning basedregression algorithm to predict which during which time windows and atwhich location an action is most likely to be completed. The scoringengine 206 can calculate the confidence score based on the featuresdetermined by the feature identifier 208. Based on the confidencelevels, the scheduling engine 210 can select during which time windowand at which location the notification generator 204 should send anotification to a respective client device 212. The machine learningmodel can use reinforcement learning techniques to update the model asadditional actions are completed.

In one example, the action generator 216 can generate a workflow with aplurality of actions. For the workflow's actions, the scoring engine 206can identify different time windows and/or locations when the action canbe completed based on the identified features. The scoring engine 206can, for each of the plurality of time windows, calculate a confidencevalue indicating a likelihood that the action will be completed duringeach of the respective plurality of time windows. The likelihood can bea probability. The scoring engine 206 can select the time window and/orgeolocation with the highest confidence value as the time window and/orgeolocation in which to transmit the notification message to the clientdevice 212.

For example, the scoring engine 206 can determine with a 99% confidencescore that the user of a first client device 212 will complete the taskbetween 9 AM and 5 PM (a first time window) and a 95% confidence scorethat the user of the first client device 212 will complete the taskbetween 2 PM and 3 PM (a second time window).

The server 202 can include a scheduling engine 210. The schedulingengine 210 can be any script, file, program, application, set ofinstructions, or computer-executable code, that is configured to enablea computing device on which the scheduling engine 210 is executed toselect transmission parameters for action notifications. Thenotification generator 204 can transmit the notifications to therespective client devices 212 based on the transmission parameters. Thetransmission parameters can indicate during which time window and/or atwhich geolocation the notification generator 204 should transmit thenotification to the client device 212.

The scheduling engine 210 can be configured to select a time windowand/or geolocation from the plurality of time windows for one of theplurality of device locations based at least on the confidence value ofthe time window. For example, the scheduling engine 210 can select thetime window and/or geolocation that has the highest confidence score.The scheduling engine 210 can select the time window and/or geolocationbased on at least the time window duration and the confidence score. Forexample, a first time window may have a duration of 8 hours and aconfidence score that the action will be completed during the first timewindow of 99%. A second time window may have a duration of 1 hour and aconfidence score of 95%. The scheduling engine 210 can negatively weighttime windows with a long time duration. Continuing the previous example,the scheduling engine 210 can select the second time window because theconfidence score associated with the second time window is similarconfidence score of the first time window, but the second time window ismuch shorter.

FIG. 3 illustrates a block diagram of an example method 300 to reducethe time to complete distributed processes. The method 300 can includegenerating a notification message, which can also be referred to as anotification (BLOCK 302). Also referring to FIG. 1, the server 202 cangenerate a workflow that includes a plurality of actions. The method 300can be repeated for each of the actions in the distributed processworkflow.

The method 300 can include determining features (BLOCK 304). The server202 can determine a plurality of features associated with each of theactions in the distributed process workflow. The action features can befeatures specifically of the action and/or features of the client device212 or user assigned to the action. The action features can include atleast one of location information, action duration, historical usage, atime zone, or a user designation. The location information can indicatewhere the action should be completed. For example, a user may usemultiple client devices 212 at different locations or have a clientdevice 212 (such as a laptop or mobile device) that the user can use atdifferent locations. Some actions may only be able to be completed whenthe user is in a specific location and the location information can be ageolocation associated with that specific location. The action durationcan be predictions of how long the action is predicted to take tocomplete. The durations can be specific times or time windows (e.g., 30minutes or between about 1 hour and about 2 hours) or the durations canbe general descriptors of the time duration (e.g., short, medium, orlong time commitment).

The method 300 can include selecting time windows (BLOCK 306). Theserver 202 can select, for each action, plurality of time windows duringwhich the assigned client device 212 or user can complete the action. Insome implementations, if the action can be completed at multiple devicesor geolocations, the server 202 can select time windows for each of themultiple devices or geolocations. The server 202 can select the timewindows by binning times before the action's due date based on theaction duration. For example, if the action duration is 1 hour, theserver 202 can generate a plurality of 1 hour time windows prior to theactions due date. The selected time windows can be the same size as theaction duration or can be longer. For example, the server 202 can select4 hour time windows for an action with a 1 hour duration.

The time windows can be based on historical data associated with theaction type and user (or client device 212) to which the action isassigned. For example, the server 202 can use a machine learningalgorithm to determine when and at what geolocations a user is likely tocomplete an action. For example, the server 202 can determine that auser completes most actions between 9 AM and 5 PM and the server 202 canindicate 9 AM to 5 PM as a first time window. The server 202 candetermine that the user completes a relatively high percentage of theactions between 2 PM and 3 PM and can indicate 2 PM to 3 PM as a secondtime window. The server 202 can also generate time windows for differentgeographical locations. For example, the server 202 can determine thatthe user completes a higher percentages of actions at a secondgeolocation between 10 AM and 11 AM.

The method 300 can include determining a confidence score for the timewindows (BLOCK 308). The method 300 can include determining, for each ofthe plurality of time windows, a confidence value indicating alikelihood a given action will be completed during the respective timewindow. The server 202 can calculate a confidence score for each of thetime windows or only a portion of the time windows determined at BLOCK306. For example, the server 202 may interface with a calendaring systemand may not calculate confidence scores for windows that overlap withschedule appointments of a user associated with the assigned clientdevice 212 or during time windows to which actions have already beenassigned. In this example, the server 202 may discard those time windowsas possible time windows that can be selected for the transmission ofthe notification. The confidence score for each of the time windows canalso be based on a client device 212 location (or predicted location).The client device 212 can be a mobile device that the user could movebetween a first location and a second location. The server 202 canassign a higher confidence score to a first time window that isassociated with the first location because the server 202 determines,based on historical data, that the user completes a greater percentageof actions when at the first location.

The method 300 can include selecting a time window (BLOCK 310). Theserver 202 can select a time window from the plurality of time windowsfor one of the plurality of device locations based at least on theconfidence value of the time window. The server 202 can select the timewindow and/or geolocation based on which time window and/or geolocationhas the highest confidence score. The server 202 can select the timewindow and/or geolocation based on a confidence score that is weightedbased on the duration of the time window. Shorter duration time windowscan be weighted higher than longer duration time windows. For example, a1 hour time window with a 95% confidence score can be selected over an 8hour time window with a 99% confidence score.

Once a time window is selected, the method 300 can include determiningif the time window is below a threshold (BLOCK 312). The threshold canbe a time duration threshold. At BLOCK 312, the server 202 can determineif the time window is short in duration or long in duration. Thethreshold can be about 10 minutes, about 30 minutes, about 1 hours,about 2 hours, about 3 hours, or about 4 hours. The server 202 canclassify time windows below the threshold as relatively “short” timewindows and time windows above the threshold as relatively “long” timewindows.

If the time window is below the threshold, the method 300 can includedetermining if the device is at the location (BLOCK 316). The server 202can poll or request the client device 212 at predetermined intervals forthe client device's location. In some implementations, the client device212 can transmit an indication of its location to the server 202 atpredetermined intervals or when the location updates. The server 202 mayonly check the client device location against the location associatedwith the action once the within the time window identified by the timewindow selected at BLOCK 310.

When the time window is below the threshold, the server 202 can hold thenotification message until the client device 212 reaches the geolocationassociated with the time window because it can be the location thatinfluences the completion of the task more than the time. For example, amanager (e.g., the user) may complete actions upon visiting a specificsite the manger oversees. In this example, the time window may berelatively short because the manager completes the actions shortly afterarriving at the specific site. In this example, the server 202 candetermine that the site (e.g., the geolocation) is more influential inpredicting when the action will be completed than the specific timewindow.

If the time window is above the threshold, the method 300 can includetransmitting the message based on time (BLOCK 314). The server 202 cantransmit the notification message based on the time window selected atBLOCK 310. When transmitting the notification message based on time, theserver 202 can transmit the notification message at the beginning, end,or during the time window.

In some implementations, when transmitting the notification message tothe client device 212 (at BLOCKS 314 or 320), the server 202 canprefetch content (or more generally, data) associated with the action.When prefetching the data, the server 202 can retrieve the data andstore the data in a buffer so that the date can be access more quicklywhen the client device 212 requests the data in completing the actionassociated with the notification message. In some implementations, whenprefetching the data, the server 202 can retrieve the data and transmitthe data to the client device 212 to which the notification message wasor will be transmitted. By prefetching the data to the client device212, the client device 212 (or user thereof) can begin working on thedata once the notification message is selected or activated. Forexample, the action can be to review an electronic document. Whentransmitting the notification message to the client device 212, theserver 202 can prefetch the electronic document to the client device212. When the user selects the notification message to review theelectronic document, the user can immediately begin to review theprefetched document rather than having to wait to download the documentand then review the document once the download is complete.

If at BLOCK 316, the device is within the location, the method 300 caninclude transmitting the notification message to the client device(BLOCK 320). The server 202 can transmit the notification message to theclient device 212 once it is within the location and at a time after thestart of the time window. The server 202 can transmit the notificationmessage to client device 212 via a network. The notification message canbe a text message, email, SMS, push notification, chat message, or otherform of electronic communication.

If at BLOCK 316 the device is not within the location, the server cancheck if the time window is exceeded (BLOCK 318). If the time window isnot exceeded (e.g., the current time is not after the end time of thetime window), the method 300 can include returning to BLOCK 316 todetermine if client device 212 is within the location. The method 300can include a pause or delay before returning to BLOCK 316. For example,after BLOCK 318, the server 202 may pause for 1, 5, 10, 15, or 30minutes before repeating BLOCK 316 and checking whether the clientdevice 212 is within the device location. In some implementations, theserver 202 may repeat BLOCK 316 and check if the device is at thelocation based on receiving an updated location for the client device212. For example, after completing the check to determine if the timewindow is exceeded, the method 300 can pause at BLOCK 318 until theserver 202 receives an indication of an updated device location. If anupdated client device location is received before the end of the timewindow the server 202 can repeat BLOCK 316. If the server 202 does notreceive an updated location from the client device 212, the method 300can continue to (BLOCK 314).

Based on transmitting the message to the client device 212 at BLOCKS 314and 320, the method 300 can include determining if there are additionalactions in the workflow (BLOCK 322). If there are not additional actionsin the workflow, the method 300 can end.

If there are additional actions in the workflow, the method 300 canreceive a completion message (BLOCK 324). Before transmitting the nextaction to a client device 212, the server 202 can wait until receiving acompletion message from the client device 212 to which the notificationmessage was transmitted at BLOCKS 314 or 320. In some implementations,the server 202 only pauses at BLOCK 324 if the action associated withthe notification transmitted at BLOCKS 314 or 320 was flagged as arequired action before notifications relating to subsequent actionscould be transmitted to respect client devices 212. If the actionassociated with the notification transmitted at BLOCKS 314 or 320 wasnot marked as required, the method 300 can continue to BLOCK 302 torepeat the method 300 without waiting for a completion message to bereceived.

It should be understood that the systems described above may providemultiple ones of any or each of those components and these componentsmay be provided on either a standalone machine or, in some embodiments,on multiple machines in a distributed system. The systems and methodsdescribed above may be implemented as a method, apparatus or article ofmanufacture using programming and/or engineering techniques to producesoftware, firmware, hardware, or any combination thereof. In addition,the systems and methods described above may be provided as one or morecomputer-readable programs embodied on or in one or more articles ofmanufacture. The term “article of manufacture” as used herein isintended to encompass code or logic accessible from and embedded in oneor more computer-readable devices, firmware, programmable logic, memorydevices (e.g., EEPROMs, ROMs, PROMs, RAMs, SRAMs, etc.), hardware (e.g.,integrated circuit chip, Field Programmable Gate Array (FPGA),Application Specific Integrated Circuit (ASIC), etc.), electronicdevices, or a computer readable non-volatile storage unit (e.g., CD-ROM,USB Flash memory, hard disk drive, etc.). The article of manufacture maybe accessible from a file server providing access to thecomputer-readable programs via a network transmission line, wirelesstransmission media, signals propagating through space, radio waves,infrared signals, etc. The article of manufacture may be a flash memorycard or a magnetic tape. The article of manufacture includes hardwarelogic as well as software or programmable code embedded in a computerreadable medium that is executed by a processor. In general, thecomputer-readable programs may be implemented in any programminglanguage, such as LISP, PERL, C, C++, C#, PROLOG, or in any byte codelanguage such as JAVA. The software programs may be stored on or in oneor more articles of manufacture as object code.

While various embodiments of the methods and systems have beendescribed, these embodiments are illustrative and in no way limit thescope of the described methods or systems. Those having skill in therelevant art can effect changes to form and details of the describedmethods and systems without departing from the broadest scope of thedescribed methods and systems. Thus, the scope of the methods andsystems described herein should not be limited by any of theillustrative embodiments and should be defined in accordance with theaccompanying claims and their equivalents.

What is claimed:
 1. A system comprising a memory storing processorexecutable instructions and one or more processors to: generate anotification message indicating a first action to be performed in adistributed process; identify a plurality of features associated withthe first action to be performed in the distributed process; select aplurality of time windows for each of a plurality of device locationsbased at least on the plurality of features; determine a confidencevalue for each of the plurality of time windows, the confidence valueindicating a likelihood of the first action being completed during eachof the respective plurality of time windows and at least one devicelocation of the plurality of device locations associated with the firstaction; select a time window from the plurality of time windows for oneof the plurality of device locations based at least on the confidencevalue of the time window; transmit the notification message to a devicelocated at the one of the plurality of device locations after a starttime of the time window; determine a time duration of the time window;and hold the notification message until a predetermined device entersthe one of the plurality of device locations based on the time durationbeing below a predetermined threshold.
 2. The system of claim 1, furthercomprising the one or more processors to: determine the predetermineddevice is not within the one of the plurality of device locations at theend of the time window; and transmit the notification message to thedevice at the end of the time window.
 3. The system of claim 1, furthercomprising the one or more processors to: prefetch content associatedwith the first action to the device before the start time of the timewindow.
 4. The system of claim 1, further comprising the one or moreprocessors to: receive location information of the device; and selectthe time window from the plurality of time windows based on the locationinformation of the device.
 5. The system of claim 1, further comprisingthe one or more processors to: generate a second notification messageindicating a second action to be performed in the distributed process;transmit the second notification message to a second device; andtransmit a third notification message indicating a third action to beperformed in the distributed process to a third device before receivingan indication that the second device completed the second action.
 6. Thesystem of claim 1, further comprising the one or more processors to:select a second time window from the plurality of time windows, whereinthe second time window has a time duration shorter than the time windowand is associated with a second device location; and transmit thenotification message to a second device at the second device location.7. The system of claim 1, further comprising the one or more processorsto: transmit the notification message to the device located at the oneof the plurality of device locations based on not receiving anindication that the device at the second device location completed thesecond action.
 8. The system of claim 1, wherein the plurality offeatures comprise at least one of location information, an actionduration, a historical usage, a time zone, or a user designation.
 9. Thesystem of claim 1, wherein the confidence value for each of theplurality of time windows at each of the plurality of device locationsis generated using a machine learning based regression algorithm.
 10. Amethod comprising: generating a notification message indicating a firstaction to be performed in a distributed process; determining a pluralityof features associated with the first action to be performed in thedistributed process; select a plurality of time windows for each of aplurality of device locations based at least on the plurality offeatures; determining a confidence value for each of the plurality oftime windows, the confidence value indicating a likelihood of the firstaction being completed during each of the respective plurality of timewindows and at at least one device location of the plurality of devicelocations associated with the first action; selecting a time window fromthe plurality of time windows for one of the plurality of devicelocations based at least on the confidence value of the time window;transmitting the notification message to a device located at the one ofthe plurality of device locations after a start time of the time window;determining a time duration of the time window; and holding thenotification message until a predetermined device enters the one of theplurality of device locations based on the time duration being below apredetermined threshold.
 11. The method of claim 10, further comprising:determining the predetermined device is not within the one of theplurality of device locations at the end of the time window; andtransmitting the notification message to the device at the end of thetime window.
 12. The method of claim 10, further comprising: prefetchingcontent associated with the first action to the device before the starttime of the time window.
 13. The method of claim 10, further comprising:receiving location information of the device; and selecting the timewindow from the plurality of time windows based on the locationinformation of the device.
 14. The method of claim 10, furthercomprising: generating a second notification message indicating a secondaction to be performed in the distributed process; transmitting thesecond notification message to a second device; and transmitting a thirdnotification message indicating a third action to be performed in thedistributed process to a third device before receiving an indicationthat the second device completed the second action.
 15. The method ofclaim 10, further comprising: selecting a second time window from theplurality of time windows, wherein the second time window has a timeduration shorter than the time window and is associated with a seconddevice location; and transmitting the notification message to a seconddevice at the second device location.
 16. The method of claim 10,further comprising: transmitting the notification message to the devicelocated at the one of the plurality of device locations based on notreceiving an indication that the device at the second device locationcompleted the second action.
 17. The method of claim 10, wherein theplurality of features comprise at least one of location information, anaction duration, a historical usage, a time zone, or a user designation.18. The method of claim 10, wherein the confidence value for each of theplurality of time windows at each of the plurality of device locationsis generated using a machine learning based regression algorithm.